The ultimate steganalysis benchmark?
Proceedings of the 9th workshop on Multimedia & security
Weighted Stego-Image Steganalysis for JPEG Covers
Information Hiding
A fusion of maximum likelihood and structural steganalysis
IH'07 Proceedings of the 9th international conference on Information hiding
Multi-party covert communication with steganography and quantum secret sharing
Journal of Systems and Software
Quantitative steganalysis of LSB embedding in JPEG domain
Proceedings of the 12th ACM workshop on Multimedia and security
Quantitative structural steganalysis of Jsteg
IEEE Transactions on Information Forensics and Security
| Hi-index | 0.00 |
This paper considers the least squares method (LSM) for estimation of the length of payload embedded by least-significant bit replacement in digital images. Errors in this estimate have already been investigated empirically, showing a slight negative bias and substantially heavy tails (extreme outliers). In this paper, (approximations for) the estimator distribution over cover images are derived: this requires analysis of the cover image assumption of the LSM algorithm and a new model for cover images which quantifies deviations from this assumption. The theory explains both the heavy tails and the negative bias in terms of cover-specific observable properties, and suggests improved detectors. It also allows the steganalyst to compute precisely, for the first time, a p-value for testing the hypothesis that a hidden payload is present. This is the first derivation of steganalysis estimator performance